The present invention relates to early detection of a general disease state in a patient. The present invention also relates to discrimination (differentiation) between specific disease states in their early stages.
Early detection of a specific disease state can greatly improve a patient's chance for survival by permitting early diagnosis and early treatment while the disease is still localized and its pathologic effects limited anatomically and physiologically. Two key evaluative measures of any test or disease detection method are its sensitivity (Sensitivity=True Positives/(True Positives+False Negatives) and specificity (Specificity=True Negatives/(False Positives+True Negatives), which measure how well the test performs to accurately detect all affected individuals without exception, and without falsely including individuals who do not have the target disease. Historically, many diagnostic tests have been criticized due to poor sensitivity and specificity.
Sensitivity is a measure of a test's ability to detect correctly the target disease in an individual being tested. A test having poor sensitivity produces a high rate of false negatives, i.e., individuals who have the disease but are falsely identified as being free of that particular disease. The potential danger of a false negative is that the diseased individual will remain undiagnosed and untreated for some period of time, during which the disease may progress to a later stage wherein treatments, if any, may be less effective. An example of a test that has low sensitivity is a protein-based blood test for HIV. This type of test exhibits poor sensitivity because it fails to detect the presence of the virus until the disease is well established and the virus has invaded the bloodstream in substantial numbers. In contrast, an example of a test that has high sensitivity is viral-load detection using the polymerase chain reaction (PCR). High sensitivity is achieved because this type of test can detect very small quantities of the virus (see Lewis, D. R. et al. “Molecular Diagnostics: The Genomic Bridge Between Old and New Medicine: A White Paper on the Diagnostic Technology and Services Industry” Thomas Weisel Partners, Jun. 13, 2001).
Specificity, on the other hand, is a measure of a test's ability to identify accurately patients who are free of the disease state. A test having poor specificity produces a high rate
Specificity, on the other hand, is a measure of a test's ability to identify accurately patients who are free of the disease state. A test having poor specificity produces a high rate of false positives, i.e., individuals who are falsely identified as having the disease. A drawback of false positives is that they force patients to undergo unnecessary medical procedures treatments with their attendant risks, emotional and financial stresses, and which could have adverse effects on the patient's health. A feature of diseases which makes it difficult to develop diagnostic tests with high specificity is that disease mechanisms often involve a plurality of genes and proteins. Additionally, certain proteins may be elevated for reasons unrelated to a disease state. An example of a test that has high specificity is a gene-based test that can detect a p53 mutation. A p53 mutation will never be detected unless there are cancer cells present (see Lewis, D. R. et al. “Molecular Diagnostics: The Genomic Bridge Between Old and New Medicine: A White Paper on the Diagnostic Technology and Services Industry” Thomas Weisel Partners, Jun. 13, 2001).
Cellular markers are naturally occurring molecular structures within cells that can be discovered and used to characterize or differentiate cells in health and disease. Their presence can be detected by probes, invented and developed by human beings, which bind to markers enabling the markers to be detected through visualization and/or quantified using imaging systems. Four classes of cell-based marker detection technologies are cytopathology, cytometry, cytogenetics and proteomics, which are identified and described below.
Cytopathology relies upon the visual assessment by human experts of cytomorphological changes within stained whole-cell populations. An example is the cytological screening and cytodiagnosis of Papanicolaou-stained cervical-vaginal specimens by cytotechnologists and cytopathologists, respectively. Unlike cytogenetics, proteomics and cytometry, cytopathology is not a quantitative tool. While it is the state-of-the-art in clinical diagnostic cytology, it is subjective and the diagnostic results are often not highly sensitive or reproducible, especially at early stages of cancer (e.g., ASCUS, LSIL).
Tests that rely on morphological analyses involve observing a sample of a patient's cells under a microscope to identify abnormalities in cell and nuclear shape, size, or staining behavior. When viewed through a microscope, normal mature epithelial cells appear large and well differentiated, with condensed nuclei. Cells characterized by dysplasia, however, may be in a variety of stages of differentiation, with some cells being very immature. Finally, cells characterized by invasive carcinoma often appear undifferentiated, with very little cytoplasm and relatively large nuclei.
A drawback to diagnostic tests that rely on morphological analyses is that cell morphology is a lagging indicator. Since form follows function, often the disease state has already progressed to a critical stage by the time the disease becomes evident by morphological analysis. The initial stages of a disease involve chemical changes at a molecular level. Changes that are detectable by viewing cell features under a microscope are not apparent until later stages of the disease. Therefore, tests that measure chemical changes on a molecular level, referred to as “molecular diagnostic” tests, are more likely to provide early detection than tests that rely on morphological analyses alone.
Cytometry is based upon the flow-microfluorometric instrumental analysis of fluorescently stained cells moving in single file in solution (flow cytometry) or the computer-aided microscope instrumental analysis of stained cells deposited onto glass microscope slides (image cytometry). Flow cytometry applications include leukemia and lymphoma immunophenotyping. Image cytometry applications include DNA ploidy, Malignancy-Associated Changes (MACs) and S-phase analyses. The flow and image cytometry approaches yield quantitative data characterizing the cells in suspension or on a glass microscope slide. Flow and image cytometry can produce good marker detection and differentiation results depending upon the sensitivity and specificity of the cellular stains and flow/image measurement features used.
Malignancy-Associated Changes (MACs) have been qualitatively observed and reported since the early to mid-1900's (O C Gruner: “Study of the changes met with leukocytes in certain cases of malignant disease” in Brit J Surg 3: 506-522, 1916) (H E Neiburgs, F G Zak, D C Allen, H Reisman, T Clardy: “Systemic cellular changes in material from human and animal tissues” in Transactions, 7th Ann Mtg Inter Soc Cytol Council, pp 137-144, 1959). From the mid-1900's through 1975, MACs were documented in independent qualitative histology and cytology studies in buccal mucosa and buccal smears (Nieburgs, Finch, Klawe), duodenum (Nieburgs), liver (Elias, Nieburgs), megakaryocytes (Ramsdahl), cervix (Nieburgs, Howdon), skin (Kwitiken), blood and bone marrow (Nieburgs), monocytes and leukocytes (van Haas, Matison, Clausen), and lung and sputum (Martuzzi and Oppen Toth). Before 1975 these qualitative studies reported MAC-based sensitivities for specific disease detection from 76% to 97% and specificities from 50% to 90%. In 1975 Oppen Toth reported a sensitivity of 76% and specificity of 81% in a qualitative sputum analysis study.
Quantitative observations regarding MAC-based probe analysis began two to three decades ago (H Klawe, J Rowinski: “Malignancy associated changes (MAC) in cells of buccal smears detected by means of objective image analysis” in Acta Cytol 18: 30-33, 1974) (G L Wied, P H Bartels, M Bibbo, J J Sychra: “Cytomorphometric markers for uterine cancer in intermediate cells” in Analyt Quant Cytol 2: 257-263, 1980) (G Burger, U Jutting, K Rodenacker: “Changes in benign population in cases of cervical cancer and its precursors” in Analyt Quant Cytol 3: 261-271, 1981). MACs were documented in independent quantitative histology and cytology studies in buccal mucosa and smears Klawe, Burger), cervix (Wied, Burger, Bartels, Vooijs, Reinhardt, Rosenthal, Boon, Katzke, Haroske, Zahniser), breast (King, Bibbo, Susnik), bladder and prostate (Sherman, Montironi), colon (Bibbo), lung and sputum (Swank, MacAulay, Payne), and nasal mucosa (Reith) studies with MAC-based sensitivities from 70% to 89% and specificities from 52% to 100%. Marek and Nakhosteen showed (1999, American Thoracic Society annual meeting) the results from two quantitative pulmonary studies showing (a) sensitivity of 89% and specificity of 92%, and (b) sensitivity of 91% and specificity of 100%.
Clearly, Malignancy-Associated Changes (MACs) are potentially useful probes that result from the image-cytometry marker detection technology. MAC-based features from DNA-stained nuclei can be used in conjunction with other molecular diagnostic probes to create optimized molecular diagnostic panels for the detection and differentiation of lung cancer and other disease states.
Cytogenetics detects specific chromosome-based intracellular changes using, for example, in situ hybridization (ISH) technology. ISH technology can be based upon fluorescence (FISH), multi-color fluorescence (M-FISH), or light-absorption-based chromogenics imaging (CHRISH) technologies. The family of ISH technologies uses DNA or RNA probes to detect the presence of the complementary DNA sequence in cloned bacterial or cultured eukaryotic cells. FISH technology can, for example, be used for the detection of genetic abnormalities associated with certain cancers. Examples include probes for Trisomy 8 and HER-2 neu. Other technologies such as polymerase chain reactions (PCR) can be used to detect B-cell and T-cell gene rearrangements. Cytogenetics is a highly specific marker detection technology since it detects the causative or “trigger” molecular event producing a pathology condition. It may be less sensitive than the other marker detection technologies because fewer events may be present to detect. In situ hybridization (ISH) is a molecular diagnostic method uses gene-based analyses to detect abnormalities on the genetic level such as mutations, chromosome errors or genetic material inserted by a specific pathogen. For example, in situ hybridization may involve measuring the level of a specific mRNA by treating a sample of a patient's cells with labeled primers designed to hybridize to the specific mRNA, washing away unbound primers and measuring the signal of the label. Due to the uniqueness of gene sequences, a test involving the detection of gene sequences will likely have a high specificity, yielding very few false positives. However, because the amount of genetic material in a sample of cells may be very low, only a very weak signal may be obtained. Therefore, in situ hybridization tests that do not employ pre-amplification techniques will likely have a poor specificity, yielding many false negatives.
Proteomics depends upon cell characterization and differentiation resulting from the over-expression, under-expression, or presence/absence of unique or specific proteins in populations of normal or abnormal cell types. Proteomics includes not only the identification and quantification of proteins, but also the determination of their localization, modifications, interactions, chemical activities, and cellular/extracellular functions. Immunochemistry (immunocytochemistry in cells and immunohistochemistry (IHC) in tissues) is the technology used, either qualitatively or quantitatively (QIHC) to stain antigens (i.e., proteomes) using antibodies. Immunostaining procedures use a dye as the detection indicator. Examples of IHC applications include analyses for ER (estrogen receptor), PR progesterone receptor), p53 tumor suppressor genes, and EGRF prognostic markers. Proteomics is typically a more sensitive marker detection technology than cytogenetics because there are often orders of magnitude more protein molecules to detect using proteomics than there are cytogenetic mutations or gene-sequence alterations to detect using cytogenetics. However, proteomics may have a poorer specificity than the cytogenetic marker detection technology since multiple pathologies may result in similar changes in protein over-expression or under-expression. Immunochemistry involves histological or cytological localization of immunoreactive substances in tissue sections or cell preparations, respectively, often utilizing labeled antibodies as probe reagents. Immunochemistry can be used to measure the concentration of a disease marker (specific protein) in a sample of cells by treating the cells with an agent such as a labeled antibody (probe) that is specific for an epitope on the disease marker, then washing away unbound antibodies and measuring the signal of the label. Immunochemistry is based on the property that cancer cells possess different levels of certain disease markers than do healthy cells. The concentration of a disease marker in a cancer cell is generally large enough to produce a large signal. Therefore, tests that rely on immunochemistry will likely have a high sensitivity, yielding few false negatives. However, because other factors in addition to the disease state may cause the concentration of a disease marker to become raised or lowered, tests that rely on immunochemical analysis of a specific disease marker will likely have poor specificity, yielding a high rate of false positives.
The present invention provides a noninvasive disease state detection and discrimination method with both high sensitivity and high specificity. The method involves contacting a cytological sample suspected of containing diseased cells with a panel of probes comprising a plurality of agents, each of which quantitatively binds to a specific disease marker, and detecting and analyzing the pattern of binding of the probe agents. The present invention also provides methods of constructing and validating a panel of probes for detecting a specific disease (or group of diseases) and discriminating among its various disease states. Illustrative panels for detecting lung cancer and discriminating among different types of lung cancer are also provided.
A human disease results from the failure of the human organism's adaptive mechanisms to neutralize external or internal insults which result in abnormal structures or functions within the body's cells, tissues, organs or systems. Diseases can be grouped by shared mechanisms of causation as illustrated below, in Table 1.
TABLE 1Classes of DiseasesExamples of Disease StatesAllergyAdverse reactions to foods and plantsCardiovascularHeart failure, atherosclerosisDegenerative (neurologicalAlzheimer's and Parkinson'sand muscular)DietNon-nutritional substances andexcess/imbalanced nutritionHereditarySickle cell anemia, cystic fibrosisImmuneHIV and autoimmuneInfectionViral, bacterial, fungal, parasiticMetabolicDiabetesMolecular and cell biologyCancer (neoplasia)Toxic insultsAlcohol, drugs, environmentalmutagens and carcinogensTraumaBodily injury from automobile collision
Disease states are either caused by or result in abnormal changes (i.e., pathological conditions) at a subcellular, cellular, tissue, organ, or human anatomic or physiological system level. Many disease states (e.g., lung cancer) are characterized by abnormal changes at a subcellular or cellular level. Specimens (e.g., cervical PAP smears, voided urine, blood, sputum, colonic washings) can be collected from patients with suspected disease states to diagnose those patients for the presence and type of the disease state. Molecular pathology is the discipline that attempts to identify and diagnostically exploit the molecular changes associated with these cell-based diseases.
Lung cancer is an illustrative example of a disease state in which screening of high-risk populations and at-risk individuals can be performed using diagnostic tests (e.g., molecular diagnostic panel assays) to detect the presence of the disease state . Also, for patients in which lung cancer or other disease states have been detected by these means, related diagnostic tests can be employed to differentiate the specific disease state from related or co-occurring disease states. For example, in this lung cancer illustration, additional molecular diagnostic panel assays may indicate the probabilities that the patient's disease state is consistent with one of the following types of lung cancer: (a) squamous cell carcinoma of the lung, (b) adenocarcinoma of the lung, (c) large cell carcinoma of the lung, (d) small cell carcinoma of the lung, or (e) mesothelioma. Early detection and differentiation of cell-based disease states is a hypothesized means to improve patient outcomes.
Cancer is a neoplastic disease the natural course of which is fatal. Cancer cells, unlike benign tumor cells, exhibit the properties of invasion and metastasis and are highly anaplastic. Cancer includes the two broad categories of carcinoma and sarcoma, but in normal usage it is often used synonymously with carcinoma. According to the World Health Organization (WHO), cancer affects more than 10 million people each year and is responsible for in excess of 6.2 million deaths.
Cancer is, in reality, a heterogeneous collection of diseases that can occur in virtually any part of the body. As a result, different treatments are not equally effective in all cancers or even among the stages of a specific type of cancer. Advances in diagnostics (e.g., mammography, cervical cytology, and serum PSA testing) have, in some cases, allowed for the detection of early-stage cancer when there are a greater number of treatment options, and therapies tend to be more effective. In cases where a solid tumor is small and localized, surgery alone may be sufficient to produce a cure. However, in cases where the tumor has spread, surgery may provide, at best, only limited benefits. In such cases the addition of chemotherapy and/or radiation therapy may be used to treat metastatic disease. While somewhat effective in prolonging life, treatment of patients with metastatic disease rarely produces a cure. Even through there may be an initial response, with time the disease progresses and the patient ultimately dies from its effects and/or from the toxic effects of the treatments.
While not proven, it is generally accepted that early detection and treatment will reduce the morbidity, mortality and cost of cancer. Early detection will, in many cases, permit treatment to be initiated prior to metastasis. Furthermore, because there are a greater number of treatment options, there is a higher probability of achieving a cure or significant improvement in long-term survival.
Developing a test that can be used to screen an “at-risk” population has long been a goal of health practitioners. While there have been some successes such as mammography for breast cancer, PSA testing for prostate cancer, and the PAP smear for cervical cancer, in most cases cancer is detected at a relatively late stage where the patient is symptomatic and the disease is almost always fatal. For most cancers, no test or combination of tests has exhibited the necessary sensitivity and specificity to permit cost-effective identification of patients with early stage disease.
For a cancer screening program to be successful and gain acceptance by patients, physicians, and third party payers, the test must have implied benefit (changes the outcome), be widely available and be able to be carried out readily within the framework of general healthcare. The test should be relatively noninvasive, leading to adequate compliance, have high sensitivity, and reasonable specificity and predictive value. In addition, the test must be available at relatively low cost.
For patients who are suspected of having cancer, the diagnosis must be confirmed and the tumor properly staged cytologically and clinically in order for physicians to undertake appropriate therapeutic intervention. Some tests currently being used in the diagnosis and staging of cancer, however, either lack sufficient sensitivity or specificity, are too invasive, or are too costly to justify their use as a population-based screening test. Shown below in Tables 2 and 3, for example, are estimates of sensitivity and specificity of lung cancer diagnostics and estimated costs for diagnostic tests used to detect lung cancer.
TABLE 2ESTIMATES OF SENSITIVITY AND SPECIFICITY OFLUNG CANCER DIAGNOSTICS [1]DIAGNOSTIC TESTSENSITIVITY (%)SPECIFICITY (%)Conventional Sputum Cytology51.0100.0Chest X-ray 16-85*90-95White Light Bronchoscopy48.0-80.091.1-96.8LIFE Bronchoscopy72.0 86.7Computed Tomography63.0-99.980.0-61  PET Scan88.0-92.583.0-93.0*Dependent upon the stage of the disease at the time of diagnosis 
TABLE 3ESTIMATED COSTS FOR DIAGNOSTIC TESTSUSED IN LUNG CANCER [1]DIAGNOSTIC TESTCOST ($)Sputum Cytology 90Chest X-ray 44Bronchoscopy725Computed Tomography378PET Scan 800-3000Open Biopsy12,847-14,121
The chest radiograph (X-ray) is often used to detect and localize cancer lesions due to its reasonable sensitivity, high specificity and low cost. However, small lesions are often difficult to detect and although larger tumors are relatively easy to visualize on a chest film, at the time of detection most have already metastasized. Thus, chest X-rays lack the necessary sensitivity for use as an early detection method.
Computed tomography (CT) is useful in the confirmation and characterization of pulmonary nodules and allows the detection of subtle abnormalities that are often missed on a standard chest X-ray [2]. CT, and Spiral CT methods in particular, remains the test of choice for patients who present with a prior malignant sputum cytology result or vocal chord paralysis. CT, with its improved sensitivity over the conventional chest film, has become the primary tool for imaging the central airway [3]. While capable of examining large areas, CT is subject to artifacts from cardiac and respiratory motion although improved resolution can be achieved through the use of iodinated contrast material.
Spiral CT is a more rapid and sensitive form of CT that has the potential to detect early cancer lesions more reliably than either conventional CT or X-ray. Spiral CT appears to have greatly improved sensitivity in diagnosing early disease. However, the test has relatively low specificity with a 20% false positive rate [4]. Spiral CT is also less sensitive in detecting the central lesions that represent one-third of all lung cancers. Furthermore, while the cost of the initial test is relatively low ($300), the cost of follow-up can be high. Cytology using molecular diagnostic panel assays offers significant promise as an adjunctive test with Spiral CT to improve the specificity of Spiral CT testing by minimizing false positive results through the evaluation of fine needle aspirations (FNAs) or biopsies (FNBs) from Spiral CT-suspicious pulmonary nodules.
Fluorescence bronchoscopy provides increased sensitivity over conventional white light bronchoscopy, significantly improving the detection of small lesions within the central airway [5]. However, fluorescence bronchoscopy is unable to detect peripheral lesions, it takes a long time for bronchoscopists to examine a patient's airways, and it is an expensive procedure. Additionally, the procedure is moderately invasive, creating an insurmountable barrier to its use as a population-based screening test.
Positron Emission Tomography (PET) is a highly sensitive test that utilizes radioactive glucose to identify the presence of cancer cells within the lung [6-8]. The cost of establishing a testing facility is high and there is the need for a cyclotron on site or nearby. This, coupled with the high cost of the test, has limited the use of PET scans to staging lung cancer patients rather than for early detection of the disease.
Although used for some time as a means of screening for lung cancer, sputum cytology has enjoyed only limited success due to its low sensitivity and its failure to reduce disease-specific mortality. In conventional sputum cytology, the pathologist uses characteristic changes in cellular morphology to identify malignant cells and make a diagnosis of cancer. Today only 15% of patients who are “at-risk” or who are suspected of having lung cancer undergo sputum cytology testing, and less than 5% undergo multiple evaluations [9]. A number of factors including tumor size, location, degree of differentiation, cell clumping, inefficiency of clearing mechanisms to release cells and sputum to the external environment, and the poor stability of cells within the sputum contribute to the overall poor performance of the test.
Cancer diagnostics has traditionally relied upon the detection of single molecular markers. Unfortunately, cancer is a disease state in which single markers have typically failed to detect or differentiate many forms of the disease. Thus, probes that recognize only a single marker have been shown to be largely ineffective. Exhaustive searches for “magic bullet” diagnostic tests have been underway for many decades though no universal successful magic bullet probes have been found to date.
A major premise of this invention is that cell-based cancer diagnostics and the screening, diagnosis for, and therapeutic monitoring of other disease states will be significantly improved over the state-of-the-art that uses single marker/probe analyses rather than kits of multiple, simulaneously labeled probes. This multiplexed analytical approach is particularly well suited for cancer diagnostics since cancer is not a single disease. Furthermore, this multi-factorial “panel” approach is consistent with the heterogeneous nature of cancer, both cytologically and clinically.
Key to the successful implementation of a panel approach to cell-based diagnostic tests is the design and development of optimized panels of probes that can chemically recognize the pattern of markers that characterizes and distinguishes a variety of disease states. This patent application describes an efficient and unique methodology to design and develop such novel and optimized panels.
Improved methods for specimen collection (e.g., point-of-care mixers for sputum cytology) and preparation (e.g., new cytology preservation and transportation fluids, and liquid-based cytology preparation instruments) are under development and becoming commercially available. In conjunction with existing and these emerging methods, a successful implementation of this molecular diagnostics cell-based panel assay will lead to (a) characterization of the molecular profile of malignant tumors and other disease states, (b) improved methods for early cancer and other disease state detection and differentiation, and (c) opportunities for improved clinical diagnoses, prognoses, customized patient treatments, and therapeutic monitoring.